Detecting species interactions in survey data: New approaches and applications

Principal Investigators:

Jonathan B. Shurin

Geographic variation in community structure can be driven by the physical environment, biotic interactions, stochastic factors such as colonization and disturbance history, or by interactions among all three. The question of what factors are most important in structuring communities remains highly contentious. This proposal describes work aimed at integrating techniques for detecting interspecific associations with ordination approaches for analyzing patterns of species distributions with respect to the physical environment. My goal is to generate... more

Geographic variation in community structure can be driven by the physical environment, biotic interactions, stochastic factors such as colonization and disturbance history, or by interactions among all three. The question of what factors are most important in structuring communities remains highly contentious. This proposal describes work aimed at integrating techniques for detecting interspecific associations with ordination approaches for analyzing patterns of species distributions with respect to the physical environment. My goal is to generate synthetic models of community dynamics that include biotic and abiotic processes. I will apply the new method to the analysis of a large data set of zooplankton species distributions and limnological features among lakes, and to time series data of species abundances within lakes.
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